Data governance

Unstructured data governance is the set of rules and evidence determining what file data is kept, for how long, and by whom it may be reached. It differs from database governance because files carry almost no self-description, so every rule has to be applied to attributes derived from outside the file.

Key takeaways

Unstructured data governance sets the rules and keeps the evidence for what file data is kept, for how long, and who may reach it.
Governance depends on visibility: rules can only apply to files someone knows exist.
Policies written against file attributes apply the same way wherever content is stored.

Why is data governance harder for unstructured data?

For structured data, governance decisions are enforced inside the database. For unstructured data, they have to hold across every storage system the organization uses, which is harder, because the files sit in many places and few of them carry any record of why they were kept. Governance for unstructured data therefore starts with an accurate catalog of what exists, because a policy can only be applied to data somebody can find.

What is the difference between governance and visibility?

Visibility is knowing what exists, where it sits, who owns it, and when it was last used. Governance is the set of decisions made on that basis and the proof that they were carried out. Visibility is a prerequisite. A governance program built on an incomplete picture of the estate produces policies that reach only part of it.

What is a data governance framework?

A data governance framework is the written structure that says who decides what about data: the roles, such as data owners and data stewards, the policies they apply, and the evidence that shows the policies were followed. For file data, a framework works only when each policy can name the files it covers, which takes a current record of each file’s attributes, such as owner, age, location, and retention class. Without that record, the framework describes intentions rather than practice.

How does unstructured data governance work in large organizations?

It works in layers:

Policies. A central team sets the policies, such as retention classes, sensitivity rules, and who may approve deletion.
Stewards. Each business unit names data stewards who apply those policies to its own files.
One index. Underneath both sits one current index of every file, across sites and vendors, so policies are applied to what actually exists.

At scale, governance depends less on more rules and more on knowing, for every file, what it is and who owns it.

Can governance apply wherever content is stored?

Yes, when the description of the content is independent of where it sits. Policies written against attributes, such as owner, project, retention class, or sensitivity, apply the same way on premises, in the cloud, and at the edge, as long as every location is indexed into the same catalog. Policies written against one system’s folders or features stop at that system’s edge.

How does a catalog support compliance and security work?

A catalog supplies the inventory both disciplines assume they already have: what exists, where it sits, who owns it, and when it last changed. Compliance teams use it to show that a retention rule was applied to a named set of files. Security teams use it to scope an incident and to find files whose location or permissions carry risk. It describes files by their attributes rather than their contents, which is why security teams find it easier to approve: read-only, metadata-only, within their own controls.

How do you start a data governance program for unstructured data?

Start with what you can see, then add rules:

Build an inventory of every storage system, with owners.
Name data stewards for each business area.
Agree on a few rules, such as retention periods and where sensitive data may sit.
Apply them by policy and keep a record of every action.

A small program that runs is worth more than a large framework that stays on paper.

How does Diskover help?

Diskover gives governance teams an accurate, current picture of every file across every storage system, with retention class and likely-sensitive data recorded from metadata.

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